I'll try to keep this as short as possible. I'm trying to create a bioinformatics program for our patient 'reporting' team. To preface this, examples I will be giving are just examples and not actual patient information.
The script I'm writing will take the results of a patients genetic test, take their nucleotide results via specific snps we test for.(organized via rsID from NCBI). This patient information is merged with a reference library I've made and will be compared with it. The goal is to 1.)Merge these files. 2.)Have patient nucleotide results compared to the nucleotides from the reference library. 3.) Create a "Flag" if the patients nucleotide is rare and from a small frequency percentage.
The issue I'm having, is that when running the script, after uploading the patient file and population data, I'm getting a Key Error, as its not able to find the rsID column on the patient .csv.
I'll add 2 photos of what each .csv file looks like
enter image description here population data
enter image description here patient data
Here is a short excerpt of the code
onClick('Upload Patient Files First')
patient_data = pd.read_csv(ask_path(),)
###patient_genotype = patient_data.loc[patient_data['rsID'] == rsID]['NCBI SNP Reference']
##Not using
onClick('Upload Population Frequency Data Next')
pop_ref_data = pd.read_csv(ask_path())
#Creating a dictionary of the population reference data
def pop_dict(pop_ref_data):
pop_ref_dict = {}
for _, row in pop_ref_data.iterrows():
variant_data ={}
rsID = row['rsID']
dominant_nucleotide = row['DomNucl']
recessive_nucleotide = row['RecNucl']
dominant_freq = row['DomAllele']
recessive_freq = row['RecessiveAllele']
variant_data[dominant_nucleotide]= dominant_freq
variant_data[recessive_nucleotide]= recessive_freq
pop_ref_dict[rsID] = variant_data
return pop_ref_dict
The population data is pretty straight forward. I'm getting stuck on the first check though. under the column "rsID" is where i'm getting the Key Error.
The patient data is further down on its respective CSV. I'm trying to get it to find the information under the columns 'NCBI SNP Reference' and 'Call'.
Quick Edit: These are my Traceback calls. Also, to answer another question... Yes, I'm trying to bypass all of the header info on the CSV so that I can just use the bulk information I actually need once the genotyping run is finished.
Traceback (most recent call last):
File "C:\Users\rcthu\PycharmProjects\WorkStuff\venv\lib\site-packages\pandas\core\indexes\base.py", line 3802, in get_loc
return self._engine.get_loc(casted_key)
File "pandas_libs\index.pyx", line 138, in pandas._libs.index.IndexEngine.get_loc
File "pandas_libs\index.pyx", line 165, in pandas._libs.index.IndexEngine.get_loc
File "pandas_libs\hashtable_class_helper.pxi", line 5745, in pandas._libs.hashtable.PyObjectHashTable.get_item
File "pandas_libs\hashtable_class_helper.pxi", line 5753, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'rsID'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "C:\Users\rcthu\AppData\Roaming\JetBrains\PyCharmCE2022.2\scratches\Flag Process 2.12.py", line 61, in
pop_ref_row = pop_dict(pop_ref_data)
File "C:\Users\rcthu\AppData\Roaming\JetBrains\PyCharmCE2022.2\scratches\Flag Process 2.12.py", line 41, in pop_dict
rsID = row['rsID']
File "C:\Users\rcthu\PycharmProjects\WorkStuff\venv\lib\site-packages\pandas\core\series.py", line 981, in getitem
return self._get_value(key)
File "C:\Users\rcthu\PycharmProjects\WorkStuff\venv\lib\site-packages\pandas\core\series.py", line 1089, in _get_value
loc = self.index.get_loc(label)
File "C:\Users\rcthu\PycharmProjects\WorkStuff\venv\lib\site-packages\pandas\core\indexes\base.py", line 3804, in get_loc
raise KeyError(key) from err
KeyError: 'rsID'
Process finished with exit code 1
The first thing to notice is that 'rsID' is the first key that you are calling. Looking at your data, rsID may not be what you expect since it is over an index.
You should be able to set a breakpoint before the line that breaks and run your code in debug mode. Once you're at the breakpoint you should be able to see what 'row' really is and what keys it has.
You could also just print(row) then return to get the first one.
Hope this helps.
Related
I am getting an error on one workstation when running a Python script. The script runs fine on VMs and my workstation.
pip list Shows packages are the same
Workstations are all using Python 3.10.4 64bit
This is the only workstation throwing this error.
It might be a memory issue, but the workstation has 2x4Gb RAM. I tried to chunk it out, but that did not work either. The file is barely 1Mb.
As troubleshooting, I cut the file to just 500 rows, and it ran fine. When I tried 1000 rows out of the 2500 rows in the file, it gave the same error. Interestingly the workstation cannot run the script with even just one row now.
Including error_bad_lines=False, iterator=True, chunksize=, low_memory=False have all not worked.
What is causing this error? Why did it run just fine using a few rows, but now not even with one row?
Here is the Traceback:
Traceback (most recent call last):
File "c:\Users\script.py", line 5, in <module>
data = pd.read_csv("C:/Path/file.csv", encoding='latin-1' )
File "C:\Users\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\util\_decorators.py", line 311, in wrapper
return func(*args, **kwargs)
File "C:\Users\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\io\parsers\readers.py", line 680, in read_csv
return _read(filepath_or_buffer, kwds)
File "C:\Users\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\io\parsers\readers.py", line 581, in _read
return parser.read(nrows)
File "C:\Users\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\io\parsers\readers.py", line 1250, in read
index, columns, col_dict = self._engine.read(nrows)
File "C:\Users\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\io\parsers\c_parser_wrapper.py", line 225, in read
chunks = self._reader.read_low_memory(nrows)
File "pandas\_libs\parsers.pyx", line 805, in pandas._libs.parsers.TextReader.read_low_memory
File "pandas\_libs\parsers.pyx", line 861, in pandas._libs.parsers.TextReader._read_rows
File "pandas\_libs\parsers.pyx", line 847, in pandas._libs.parsers.TextReader._tokenize_rows
File "pandas\_libs\parsers.pyx", line 1960, in pandas._libs.parsers.raise_parser_error
pandas.errors.ParserError: Error tokenizing data. C error: Expected 1 fields in line 5, saw 4
Here is the script:
# Import raw data
data = pd.read_csv("C:/Users/Script.csv", encoding='latin-1' )
# Create array to track failed cases.
data['Test Case Failed']= ''
data = data.replace(np.nan,'')
data.insert(0, 'ID', range(0, len(data)))
# Testcase 1
data_1 = data[(data['FirstName'] == data['SRFirstName'])]
ids = data_1.index.tolist()
for i in ids:
data.at[i,'Test Case Failed']+=', 1'
# There are 15 more test cases that preform similar tasks
# Total cases
failed = data[(data['Test Case Failed'] != '')]
passed = data[(data['Test Case Failed'] == '')]
failed['Test Case Failed'] =failed['Test Case Failed'].str[1:]
failed = failed[(failed['Test Case Failed'] != '')]
# Clean up
del failed["ID"]
del passed["ID"]
# Print results
failed['Test Case Failed'].value_counts()
print("There was a total of",data.shape[0], "rows.", "There was" ,data.shape[0] - failed.shape[0], "rows passed and" ,failed.shape[0], "rows failed at least one test case")
# Drop unwanted columns
redata = passed.drop(columns=['ConsCodeImpID', 'ImportID', 'Suff1', 'SRSuff2', 'Inactive',
'AddrRegion','AddrImpID', 'AddrImpID', 'AddrImpID.2', 'AddrImpID.1', 'PhoneAddrImpID',
'PhoneAddrImpID.1', 'PhoneImpID', 'PhoneAddrImpID', 'PhoneImpID', 'PhoneType.1', 'DateTo',
'SecondID', 'Test Case Failed', 'PhoneImpID.1'])
# Clean address
redata['AddrLines'] = redata['AddrLines'].str.replace('Apartment ','Apt ',regex=True)
redata['AddrLines'] = redata['AddrLines'].str.replace('Apt\\.','Apt ',regex=True)
redata['AddrLines'] = redata['AddrLines'].str.replace('APT','Apt ',regex=True)
redata['AddrLines'] = redata['AddrLines'].str.replace('nApt','Apt ',regex=True)
#There's about 100 more rows of address clean up
# Output edited dropped columns
redata.to_csv("C:/Users/cleandata.csv", index = False)
# Output failed rows
failed.to_csv("C:/Users/Failed.csv", index = False)
# Output passed rows
passed.to_csv("C:/Users/Passed.csv", index = False)
The workstation was corrupting the file, despite never opening it before running the script. I repaired the file and it worked. After reinstalling Excel, I no longer had to repair the file and could run the script as normal.
Click File > Open.
Click the location and folder that contains the corrupted workbook.
In the Open dialog box, select the corrupted workbook.
Click the arrow next to the Open button, and then click Open and
Repair.
Open and repair command
To recover as much of the workbook data as possible, pick Repair.
If Repair isn’t able to recover your data, pick Extract Data to
extract values and formulas from the workbook.
I am using the Google Cloud NL API to analyse the sentiment of some descriptions. As for some rows the error InvalidArgument: 400 The language vi is not supported for document_sentiment analysis.keeps popping up, I would like to build a way around it instead of desperately trying to find the reason why this happens and erase the responsible rows. Unfortunately, I am relatively new to Python and am not sure how to properly do it.
My code is the following:
description_list = []
sentimentscore_list=[]
magnitude_list=[]
# Create a Language client
language_client = google.cloud.language.LanguageServiceClient()
for i in range(len(description)): # use the translated description if the original description is not in English
if description_trans[i] == '':
descr = description[i]
else:
descr = description_trans[i]
document = google.cloud.language.types.Document(
content=descr,
type=google.cloud.language.enums.Document.Type.PLAIN_TEXT)
# Use Language to detect the sentiment of the text.
response = language_client.analyze_sentiment(document=document)
sentiment = response.document_sentiment
sentimentscore_list.append(sentiment.score)
magnitude_list.append(sentiment.magnitude)
# Add the description that was actually used to the description list
description_list.append(descr)
Would anyone be able to explain me how to wrap this for loop (or probably the latter part is sufficient) into the error/exception handling so that it simply "skips over" the one it can't read and continues with the next one? Also I want the 'description_list' to be only appended when the description is actually analysed (so not when it gets stuck in the error handling).
Any help is much appreciated!! Thanks :)
Edit: I was asked for a more complete error traceback:
Traceback (most recent call last):
File "<ipython-input-64-6e3db1d976c9>", line 1, in <module>
runfile('/Users/repos/NLPAnalysis/GoogleTest.py', wdir='/Users/repos/NLPAnalysis')
File "/Users/anaconda3/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py", line 710, in runfile
execfile(filename, namespace)
File "/Users/anaconda3/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py", line 101, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "/Users/repos/NLPAnalysis/GoogleTest.py", line 45, in <module>
response = language_client.analyze_sentiment(document=document)
File "/Users/anaconda3/lib/python3.6/site-packages/google/cloud/language_v1/gapic/language_service_client.py", line 180, in analyze_sentiment
return self._analyze_sentiment(request, retry=retry, timeout=timeout)
File "/Users/anaconda3/lib/python3.6/site-packages/google/api_core/gapic_v1/method.py", line 139, in __call__
return wrapped_func(*args, **kwargs)
File "/Users/anaconda3/lib/python3.6/site-packages/google/api_core/retry.py", line 260, in retry_wrapped_func
on_error=on_error,
File "/Users/anaconda3/lib/python3.6/site-packages/google/api_core/retry.py", line 177, in retry_target
return target()
File "/Users/anaconda3/lib/python3.6/site-packages/google/api_core/timeout.py", line 206, in func_with_timeout
return func(*args, **kwargs)
File "/Users/anaconda3/lib/python3.6/site-packages/google/api_core/grpc_helpers.py", line 56, in error_remapped_callable
six.raise_from(exceptions.from_grpc_error(exc), exc)
File "<string>", line 3, in raise_from
InvalidArgument: 400 The language vi is not supported for document_sentiment analysis.
I agree with ThatBird that wrapping too much code in a try-block can make debugging internal errors complicated. I would suggest utilizing python's continue keyword.
try:
# smallest block of code you foresee an error in
response = language_client.analyze_sentiment(document=document) # I think your exception is being raised in this call
except InvalidArgument as e:
# your trace shows InvalidArgument being raised and it appears you dont care about it
continue # continue to next iteration since this error is expected
except SomeOtherOkayException as e:
# this is an example exception that is also OK and "skippable"
continue # continue to next iteration
except Exception as e:
# all other exceptions are BAD and unexpected.This is a larger problem than just this loop
raise e # break the looping and raise to calling function
sentiment = response.document_sentiment
sentimentscore_list.append(sentiment.score)
magnitude_list.append(sentiment.magnitude)
# Add the description that was actually used to the description list
description_list.append(descr)
# more code here...
Essentially, you're explicitly catching Exceptions that are expected, and discarding that iteration if they occur and continuing to the next one. You should raise all other exceptions that are not expected.
In the traceback, look at the fourth line, it's the same line that is in your code and causing an exception. We always put try except around the code block that we think is going to cause an exception. Everything else is put outside the block.
try:
response = language_client.analyze_sentiment(document=document)
except InvalidArgument:
continue
# Assuming none of these would work if we don't get response?
description_list.append(descr)
sentiment = response.document_sentiment
entimentscore_list.append(sentiment.score)
magnitude_list.append(sentiment.magnitude)
# Add the description that was actually used to the description list
We try to get response from language client, it raises an exception saying InvalidArgument, we catch that. Now we know we don't need to do anything and we use continue, and move on to the next iteration.
You probably will need to import InvalidArgument like -
from google.api_core.exceptions import InvalidArgument
before using it in the code.
You are right about continue. More about continue statement and how to handle exceptions in python.
I am getting a SettingWithCopyError, and even though I have identified the problem line of code, I can't understand why the error is being raised.
The problem function is as follows:
def filter_log(df, search_string):
results = df.loc[df['Message'].str.contains(search_string)]
results.loc[:,'Duration'] = results.index.to_series().diff()
results.loc[:,'Duration'] = results['Duration'].apply(lambda x: x.total_seconds())
results = results.dropna(subset=['Duration'])
results['Day'] = results.index.floor('d')
results.loc[:,'Day'] = results['Day'].apply(lambda x: x.strftime('%Y-%m-%d'))
return results
The function takes a dataframe and a search string as in input, and returns a filtered/manipulated dataframe as the result.
The error occurs on line 3 - results.loc[:,'Duration'] = results.index.to_series().diff()
This line calculates the time increments between each dataframe row using the .diff() method on the datetime index of the input dataframe.
However, I appear to be using .loc indexing correctly, and I shouldn't be setting anything on a copy. Interestingly, the error is only raised the first time I run the script in an interactive environment (or every time I run it standalone). On runs after the first run in an interactive environment, the error does no occur.
The full stack trace is as follows:
Traceback (most recent call last):
File "<ipython-input-1-d72a02ad5f86>", line 1, in <module>
runfile('C:/00_Projects/99_Misc/aqis_log_analyser/aqis_log_analyser.py', wdir='C:/00_Projects/99_Misc/aqis_log_analyser')
File "C:\apps\Anaconda2\lib\site-packages\spyder\utils\site\sitecustomize.py", line 710, in runfile
execfile(filename, namespace)
File "C:\apps\Anaconda2\lib\site-packages\spyder\utils\site\sitecustomize.py", line 86, in execfile
exec(compile(scripttext, filename, 'exec'), glob, loc)
File "C:/00_Projects/99_Misc/aqis_log_analyser/aqis_log_analyser.py", line 137, in <module>
search_results = filter_log(log_df, search_string).loc[start:end]
File "C:/00_Projects/99_Misc/aqis_log_analyser/aqis_log_analyser.py", line 94, in filter_log
results.loc[:,'Duration'] = results.index.to_series().diff()
File "C:\apps\Anaconda2\lib\site-packages\pandas\core\indexing.py", line 179, in __setitem__
self._setitem_with_indexer(indexer, value)
File "C:\apps\Anaconda2\lib\site-packages\pandas\core\indexing.py", line 337, in _setitem_with_indexer
self.obj[key] = _infer_fill_value(value)
File "C:\apps\Anaconda2\lib\site-packages\pandas\core\frame.py", line 2331, in __setitem__
self._set_item(key, value)
File "C:\apps\Anaconda2\lib\site-packages\pandas\core\frame.py", line 2404, in _set_item
self._check_setitem_copy()
File "C:\apps\Anaconda2\lib\site-packages\pandas\core\generic.py", line 1871, in _check_setitem_copy
raise SettingWithCopyError(t)
SettingWithCopyError:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
Any suggestions as to what may be causing the error in this instance?
The root cause of a SettingWithCopyError usually appears several lines before the line mentioned in the traceback. Here, your intention is to copy a subset of df into a new DataFrame, modify this new DataFrame, and return it. Pandas isn't sure if you mean to do this, or if you intended to modify the original df.
Appending an explicit .copy() should eliminate the warning:
results = df.loc[df['Message'].str.contains(search_string)].copy()
Further reading: https://www.dataquest.io/blog/settingwithcopywarning/
I wanted to ask a question regarding file conversion.
I have a JSON file (after AMR prediction execution) that I want to covert to a TSV file based on Mykrobe-predictor scripts (json_to_tsv.py) and this is my JSON output (result_TB.json).
./json_to_tsv.py /path/to/JSON_file
When I pasted a command into the terminal, I got a IndexError at Line 78.
https://github.com/iqbal-lab/Mykrobe-predictor/blob/master/scripts/json_to_tsv.py#L78
def get_sample_name(f):
return f.split('/')[-2]
And here is the error I get:
mykrobe_version file plate_name sample drug phylo_group species lineage phylo_group_per_covg species_per_covg lineage_per_covg phylo_group_depth species_depth lineage_depth susceptibility variants (gene:alt_depth:wt_depth:conf) genes (prot_mut-ref_mut:percent_covg:depth)
Traceback (most recent call last):
File "./json_to_tsv.py", line 157, in <module>
sample_name = get_sample_name(f)
File "./json_to_tsv.py", line 78, in get_sample_name
return f.split('/')[-2]
IndexError: list index out of range
Any suggestions would be appreciated.
Looking at the code I guess they expect to call the converter with something like:
python json_to_tsv.py plate/sample1/sample1.json
Try copying your JSON file to a directory called sample1 inside a directory called plate and see if you get the same error when you call it like in the example above.
Update
The problem is indeed as described above.
Doesn't work:
python json_to_tsv.py result_TB.json
mykrobe_version file plate_name sample drug phylo_group species lineage phylo_group_per_covg species_per_covg lineage_per_covg phylo_group_depth species_depth lineage_depth susceptibility variants
(gene:alt_depth:wt_depth:conf) genes
(prot_mut-ref_mut:percent_covg:depth)
Traceback (most recent call last): File "json_to_tsv.py", line 157, in <module>
sample_name = get_sample_name(f) File "json_to_tsv.py", line 78, in get_sample_name
return f.split('/')[-2] IndexError: list index out of range
Works:
python json_to_tsv.py plate/sample/result_TB.json
mykrobe_version file plate_name sample drug phylo_group species lineage phylo_group_per_covg species_per_covg lineage_per_covg phylo_group_depth species_depth lineage_depth susceptibility variants (gene:alt_depth:wt_depth:conf) genes (prot_mut-ref_mut:percent_covg:depth)
-1 result_TB plate sample NA
I'm not sure even how to ask the question, as it seems it would require quite a lot of code to get into the details. Rather than show the code, I will discuss the behavior when I run.
I am using requests to grab information from an online database. When I run a for loop to go through all of my entries, I get an error like the one below on one of the first 20 entries (usually the first, but not always). The entries in the list are all alike (just different ID numbers). I am using sleep() to ensure that I do not go beyond my rate limit (I have tried increasing sleep to ridiculous wait times, but still get the error). What really surprises me is that it works some, and then gets stuck.... what could cause that?
Also, the code was working before, then I made a large number of edits to other code in the same file, but I didn't think I edited anything related to this.
Traceback (most recent call last):
File "C:/Users/Mark/PycharmProjects/Riot_API_Challenger_Stats/Main.py", line 233, in <module>
main()
File "C:/Users/Mark/PycharmProjects/Riot_API_Challenger_Stats/Main.py", line 212, in main
match_histories=get_match_histories(challenger_Ids+master_Ids)
File "C:/Users/Mark/PycharmProjects/Riot_API_Challenger_Stats/Main.py", line 62, in get_match_histories
match_histories[summoner_Ids[i]]=api.get_match_history_data(summoner_Ids[i])
File "C:\Users\Mark\PycharmProjects\Riot_API_Challenger_Stats\RiotAPI.py", line 52, in get_match_history_data
return self._request(api_url)
File "C:\Users\Mark\PycharmProjects\Riot_API_Challenger_Stats\RiotAPI.py", line 25, in _request
return response.json()
File "C:\Users\Mark\Anaconda3\lib\site-packages\requests\models.py", line 819, in json
return json.loads(self.text, **kwargs)
File "C:\Users\Mark\Anaconda3\lib\json\__init__.py", line 318, in loads
return _default_decoder.decode(s)
File "C:\Users\Mark\Anaconda3\lib\json\decoder.py", line 343, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
File "C:\Users\Mark\Anaconda3\lib\json\decoder.py", line 361, in raw_decode
raise ValueError(errmsg("Expecting value", s, err.value)) from None
ValueError: Expecting value: line 1 column 1 (char 0)
Here are lines 10-25 of RiotAPI
def _request(self, api_url, params={}):
args = {'api_key':self.api_key}
for key, value in params.items():
if key not in args:
args[key] = value
#requests.get accesses the URL
response = requests.get(
Consts.URL['base'].format(
proxy=self.region,
region=self.region,
url=api_url
),
params=args
)
print(response.url)
return response.json()
Here is the response:
{"matches":[{"matchId":1878534497,"region":"NA","platformId":"NA1","matchMode":"CLASSIC","matchType":"MATCHED_GAME","matchCreation":1436223958539,"matchDuration":2097,"queueType":"RANKED_SOLO_5x5","mapId":11,"season":"SEASON2015","matchVersion":"5.12.0.348","participants":[{"teamId":200,"spell1Id":4,"spell2Id":7,"championId":15,"highestAchievedSeasonTier":"UNRANKED","timeline":{"creepsPerMinDeltas":{"zeroToTen":5.699999999999999,"tenToTwenty":6.9,"twentyToThirty":7.1},"xpPerMinDeltas":{"zeroToTen":358.5,"tenToTwenty":350.0,"twentyToThirty":364.20000000000005},"goldPerMinDeltas":{"zeroToTen":365.3,"tenToTwenty":337.5,"twentyToThirty":287.5},"csDiffPerMinDeltas":{"zeroToTen":-0.7,"tenToTwenty":-1.7000000000000004,"twentyToThirty":1.0999999999999999},"xpDiffPerMinDeltas":{"zeroToTen":-0.9000000000000057,"tenToTwenty":-114.75,"twentyToThirty":-121.19999999999999},"damageTakenPerMinDeltas":{"zeroToTen":480.5,"tenToTwenty":565.3,"twentyToThirty":1258.6},"damageTakenDiffPerMinDeltas":{"zeroToTen":-147.49999999999994,"tenToTwenty":-134.69999999999996,"twentyToThirty":15.0},"role":"DUO_CARRY","lane":"BOTTOM"},"masteries":[{"masteryId":4112,"rank":4},{"masteryId":4114,"rank":1},{"masteryId":4122,"rank":3},{"masteryId":4124,"rank":1},{"masteryId":4132,"rank":1},{"masteryId":4134,"rank":3},{"masteryId":4142,"rank":2},{"masteryId":4144,"rank":1},{"masteryId":4151,"rank":1},{"masteryId":4152,"rank":3},{"masteryId":4162,"rank":1},{"masteryId":4211,"rank":2},{"masteryId":4212,"rank":2},{"masteryId":4221,"rank":1},{"masteryId":4222,"rank":3},{"masteryId":4232,"rank":1}],"stats":{"winner":false,"champLevel":14,"item0":3031,"item1":0,"item2":3142,"item3":3035,"item4":1053,"item5":3250,"item6":3342,"kills":4,"doubleKills":1,"tripleKills":0,"quadraKills":0,"pentaKills":0,"unrealKills":0,"largestKillingSpree":3,"deaths":12,"assists":5,"totalDamageDealt":184710,"totalDamageDealtToChampions":27477,"totalDamageTaken":30740,"largestCriticalStrike":684,"totalHeal":2952,"minionsKilled":237,"neutralMinionsKilled":1,"neutralMinionsKilledTeamJungle":1,"neutralMinionsKilledEnemyJungle":0,"goldEarned":12074,"goldSpent":12065,"combatPlayerScore":0.....etc.}}]}]}
It'd be helpful if you can include a snippet of your code to see how you've actually used it.
However, from the exception, I think you're trying to do a
return response.json()
at line 25 of C:\Users\Mark\PycharmProjects\Riot_API_Challenger_Stats\RiotAPI.py
but the response is not in JSON format.
You can see the raw response with
print response.text
to see the string version of the response and check that the string is in JSON format.
It would be nice if you could post the actual code. But if you are unable to do so due to confidential reasons we can surmise some information from the stack trace.
You are using some HTTP protocol (SOAP/ResT) API to get a number( or series of numbers) in JSON format. One of these ID numbers has a character that is not expected or the JSON is invalid itself. Try and print the JSON request you receive before you pass it to see which one fails. Then create a unit test and run it try to analyze it with breakpoints.
Could be some sort of hyphenated or foreign character based on the database.